Self-Organizing Neural Networks: Recent Advances and Applications

✍ Scribed by Teuvo Kohonen (auth.), Dr. Udo Seiffert, Professor Lakhmi C. Jain (eds.)

• Publisher: Physica-Verlag Heidelberg
• Year: 2002
• Tongue: English
• Leaves: 289
• Series: Studies in Fuzziness and Soft Computing 78
• Edition: 1
• Category: Library

✦ Synopsis

The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna­ tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad­ equate. It is rather the universal applicability and easy handling of the SOM. Com­ pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never­ theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the­ oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up­ to-date treatment of the field of self-organizing neural networks, which will be ac­ cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup­ porting this book and contributing the first chapter.

✦ Table of Contents

Front Matter....Pages I-XIV
Overture....Pages 1-12
Measures for the Organization of Self-Organizing Maps....Pages 13-44
Unsupervised Learning and Self-Organization in Networks of Spiking Neurons....Pages 45-73
Generative Probability Density Model in the Self-Organizing Map....Pages 75-94
Growing Multi-Dimensional Self-Organizing Maps for Motion Detection....Pages 95-120
Extensions and Modifications of the Kohonen-SOM and Applications in Remote Sensing Image Analysis....Pages 121-144
Modeling Speech Processing and Recognition in the Auditory System Using the Multilevel Hypermap Architecture....Pages 145-164
Algorithms for the Visualization of Large and Multivariate Data Sets....Pages 165-183
Self-Organizing Maps and Financial Forecasting: an Application....Pages 185-216
Unsupervised and Supervised Learning in Radial-Basis-Function Networks....Pages 217-243
Parallel Implementations of Self-Organizing Maps....Pages 245-278

✦ Subjects

Artificial Intelligence (incl. Robotics); Computation by Abstract Devices; Statistical Physics, Dynamical Systems and Complexity